Predictive Patterns Tell a Story

Data help Wittenberg University identify and help students who may be at financial risk.

By Margo Vanover Porter

Doug Schantz believes that reviewing data helps him pinpoint trends, which is one reason why Wittenberg University runs a nightly utility to capture the names of students who have an outstanding financial obligation. (Read also "On-Campus Advocates" in the November issue of Business Officer magazine.)

"We want to know if there is anything we can change or tweak institutionally to make it easier for students," says the director, office of student accounts, Wittenberg University, Springfield, Ohio. "By tracking that information, we hope to be able to identify common denominators and hone in on certain segments of our student population. We don't have an infinite amount of resources at our disposal, whether that is money, people, or time." Suppose, for example, that the data indicate that a group of student athletes are having trouble meeting their expenses. If that scenario should arise, he says, "We could look at programming that uses our coaches as a resource to help promote better financial knowledge and awareness among the student athletes."

Better Use of Resources

Shantz explains that Wittenberg tracks certain information about students with unpaid balances. "When it comes to their finances and retention," he says, "we want to recognize trends and perform predictive analysis to better align our limited resources [in ways] to make the greatest impact on our student population." To do that, the university tracks the following: